Partial-order reduction and trail improvement in directed model checking

In this paper we present work on trail improvement and partial-order reduction in the context of directed explicit-state model checking. Directed explicit-state model checking employs directed heuristic search algorithms such as A* or best-first search to improve the error-detection capabilities of explicit-state model checking. We first present the use of directed explicit-state model checking to improve the length of already established error trails. Second, we show that partial-order reduction, which aims at reducing the size of the state space by exploiting the commutativity of concurrent transitions in asynchronous systems, can coexist well with directed explicit-state model checking. Finally, we illustrate how to mitigate the excessive length of error trails produced by partial-order reduction in explicit-state model checking. In this context we also propose a combination of heuristic search and partial-order reduction to improve the length to already provided counterexamples.     

Ant colony optimization with partial order reduction for discovering safety property violations in concurrent models

In this article we analyze the combination of ACOhg, a new metaheuristic algorithm, plus partial order reduction applied to the problem of finding safety property violations in concurrent models using a model checking approach. ACOhg is a new kind of ant colony optimization algorithm inspired by the foraging behavior of real ants equipped with internal resorts to search in very large search landscapes. We here apply ACOhg to concurrent models in scenarios located near the edge of the existing knowledge in detecting property violations. The results state that the combination is computationally beneficial for the search and represents a considerable step forward in this field with respect to exact and other heuristic techniques.